Welcome to our site! EDAboard.com is an international Electronics Discussion Forum focused on EDA software, circuits, schematics, books, theory, papers, asic, pld, 8051, DSP, Network, RF, Analog Design, PCB, Service Manuals... and a whole lot more! To participate you need to register. Registration is free. Click here to register now.
Convolutional codes are widely used to encode digital data before transmission through noisy or error-prone channels. During encoding, k input bits are mapped to n output bits to give a rate k/n coded bitstream. The encoder consists of a shift register of kL stages, where L is described as the constraint length of the code.
a convolutional code is a type of error-correcting code
It is called convolution coding because it appears as though you convolve an impulse response with the input bit sequence... its because you perform modulo 2 addition on the contents of the shift register and give them in the output...
There are various types in such convolution coding...
systematic--where the input sequence is a part of the output sequence
non-systematic--where the input sequence is not a part of the output sequence
recursive--where the output of one of the modulo 2 adders is fed back to the input of the adder itself... such that it have infinite impulse response...
non-recursive--where there is no feedback... such that it have finite impulse response...
Convolution coding is error corection coding. I am agree with this but the what you have explain is called hamming code most probably. Would you give me specific defination of this ( convolution coding)
As u r performing modulo 2 addition , it is called convolution coding and the output parity bits depends on the no of message bits equal to constraint length...
Compared to linear block codes where we consider in terms of blocks of data will be send through the channel but here we can process inputs as such as they arrive. here it has the memory so that the output does not depend not only on the present input but also on the previous inputs..
Convolutional encoding with Viterbi decoding is a FEC technique that is particularly suited to a channel in which the transmitted signal is corrupted mainly by additive white gaussian noise (AWGN). You can think of AWGN as noise whose voltage distribution over time has characteristics that can be described using a Gaussian, or normal, statistical distribution, i.e. a bell curve. This voltage distribution has zero mean and a standard deviation that is a function of the signal-to-noise ratio (SNR) of the received signal. Let's assume for the moment that the received signal level is fixed. Then if the SNR is high, the standard deviation of the noise is small, and vice-versa. In digital communications, SNR is usually measured in terms of Eb/N0, which stands for energy per bit divided by the one-sided noise density.
convolutional coding is a form of error correction coding. the convolutional encoder can be considered as a shift register with desintaed outputs used to take out the encoded data. the decoding operation can be done by Viterbi algorithm.
This site uses cookies to help personalise content, tailor your experience and to keep you logged in if you register.
By continuing to use this site, you are consenting to our use of cookies.